Big Data in Healthcare

Big Data is used when speaking about the data sets that are so large and complex that common applications can’t cope with them. “Big Data” also refers to predictive, user behavior, or any other advanced analytics methods that get value from the data.

Big Data processing and analysis are taking more and more influence in the healthcare sphere. Telemedicine, wearables, and other medical devices gather a huge amount of data. To use it efficiently, practitioners require a convenient access to it, as well as its interpretation. There are a lot of examples how healthcare uses big data approaches.

Healthcare Database
Smartphones and wearables track people progress towards a healthier lifestyle, as well as monitor chronic diseases like diabetes, Parkinson’s and heart disease. This leads to the creation of huge and useful databases that can be game changers in the treatment process. Big Data can also help with epidemics tracking.

Electronic Health Records
Digital record for every patient with demographics, medical history, allergies, test results, and much more. Less paperwork and no data replication.

Real Time Alerting
Continuous health data from patient wearables sent to the cloud that can be shared with doctors and alert function in case of alarming changes.

Big Data substantially decreases costs in the healthcare industry. Forbes illustrates this tendency with the HealthConnect program created by Kaiser Permanente. It unifies records in the system and has already saved $1 billion.

Healthcare has got much improved due to personalized medicine, predictive analytics, automated documentation, digital reporting, and much more. All that has become possible thanks to the big data processing and analysis. IBM’s Watson is aiming at gathering and summarizing existing medical research for the proper treatment. The pharmaceutical collaboration resulted in the discovery that the antidepressant, Desipramine, can be used for curing of lung cancer.